1. Field of the Invention
The present invention relates to an image processing method and apparatus for quantizing a multi-valued image into a binary image, a four-valued image or the like.
2. Description of the Related Art
Hitherto, an image processing apparatus of the foregoing type, such as, for example, a color ink jet printer, inputs data formed of a multi-valued RGB data or the like via an interface, and converts the input data from RGB values to YMCK values by color conversion processing within the printer. Furthermore, the YMCK multi-valued data is converted into final binary drawing data by a binary process provided within the printer.
Since a color ink jet printer having the above-described construction is a binary display unit which is incapable of controlling the density for each pixel, an error diffusion method is generally widely used as a binarization method in order to reproduce a gradation image.
The first algorithm of the error diffusion method was introduced by Floyd and Steinberg in 1975 ("An Adaptive Algorithm for Spatial Gray Scale" in Society for Information Display 1975 Symposium Digest of Technical Papers, 1975, pp. 36-37). This method globally makes a compensation for a local error by comparing input data with a threshold value for each scanning pixel, and by feeding back an error which arises from the binarized results to the peripheral pixels which have not been processed.
FIG. 12 is a schematic block diagram illustrating the structure of a binarization process by an error diffusion method. As is shown in the figure, an adder 11 inputs an image input signal and a quantization error from an error filter 14, and outputs an addition result value after both of the input values are added to each other as its internal process (here, for the sake of convenience, the definition areas of the image input signal are assumed to be 0 and 1).
A binarization processor 12 inputs the addition result value, compares the value with a predetermined threshold value (here, assumed to be 1/2) as its internal process, and outputs, as an image output signal, "1" when the addition result value is greater than the threshold value and "0" when otherwise.
A quantization error calculation means 13 inputs the addition result value and the image output signal, calculates the difference between them as its internal process, and outputs a quantization error amount.
An error filter 14 inputs the quantization error amount, calculates the error amount corresponding to the amount of the addition of the next pixel after the quantization error amount is multiplied by a peripheral distribution ratio of the error amount, and feeds back this amount to the adder 11.
This error diffusion method, as compared with a dither matrix method, has an excellent feature in that the resolution of a reproduced image is higher.
However, in a binarization method employing an error diffusion method, there are problems: for example, geometrical interference fringes occur in a specific density area due to the influence of the frequency characteristic possessed by the system itself, causing the image quality to deteriorate considerably. This phenomenon is caused by the fact that the error diffusion system is itself formed of a closed loop structure, and this cannot be prevented because the error diffusion method itself is configured to surely distribute an error caused in each pixel to the peripheral pixels (e.g., via a peripheral distribution ratio as discussed above). As a main factor which determines the characteristics of such an error diffusion system, the characteristics of the error filter can be cited. These characteristics are a main factor which determines the pattern in which the geometrical interference fringes occur.
For this reason, some proposals have hitherto been made for improving the error filter. However, no method for providing a radical solution to such problems has yet been found in any of the proposals. For example, other patterns are used to merely change the generation pattern of the interference fringes, or even if random signals are used to erase the interference fringes, the image contains white-noise.